![]() It especially provides a platform for high-caliber academics, practitioners and PhD/Doctoral graduates to publish completed work and latest research outcomes. ![]() ![]() High quality research, survey & review articles are proposed from experts in the field, promoting insight and understanding of the state of the art, and trends in computer science and technology. ![]() It is our great pleasure to present the July 2016 issue (Volume 14 Number 7 Part I, II & III) of the International Journal of Computer Science and Information Security (IJCSIS). The platform also offers added protection against 0-day vulnerabilities and APT attacks by using its behavioural analysis techniques. An intelligent firewall separates the protected infrastructure from malicious internet traffic by telling apart malevolent Tor traffic from other benign traffic flows. As detecting Tor traffic is not a trivial task, the platform includes a dedicated module for scanning and making a risk assessment of inbound and outbound connections. In addition, when attacks that involve zombie computers come from the Dark Web, the proposed platform tries to uncover their true source, so it can inform the unsuspecting users or defer them to justice. The malware analysis component is based upon three sub-components that perform static and behavioural analysis against suspected pieces of code, documents or traffic. Our proposed implementation is based on software defined network components, and it uses artificial neural networks for protecting these critical infrastructures. This proposed implementation has been integrated into an already built platform that aims to protect an organization's geographically distributed network. This infrastructure's architecture is based on customized open-source projects. For this task, we propose a connected infrastructure that offers various types of malware analysis capabilities. In an Internet connected world, cyber security assurance is critical for protecting an organization's critical infrastructures.
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